LABSCO SUMMARY
Local designs the guide; only remote publishes it.
Both paths build and export the guide; only the hosted one deploys it and hands you a link a participant can open. Since the whole value of a survey is that someone answers it, the remote server is effectively the product and the local install is a design tool. The AI probing is the reason to prefer this over a form builder: a follow-up question written in response to what someone actually said is where the useful answers come from.
What it is
An MCP server for Feedbk, a survey product whose interviews are moderated by an AI that asks its own follow-up questions. You describe the research you want in plain language and the server turns it into a configured interview guide, detecting the right question type for each question rather than making you pick one.
What you get
- Interview design from a description — name, purpose and questions — with the question type detected and configured automatically
- AI probing built into the interview itself: the interviewer asks intelligent follow-ups based on what a participant answers, with nothing to configure
- The question types you would expect, ready to use: single-choice, multiple-choice, open-ended text, and a rating scale from very dissatisfied to very satisfied
- Guide export, available in both the local and remote setups
- Two capabilities the remote server has and the local install does not: automatic deployment to feedbk.ai, and shareable interview links you can send to participants. A local install can create and export guides but cannot publish them
Requirements
Nothing to install for the remote path — the server is at https://mcp.feedbk.ai/mcp over HTTP, added with claude mcp add --transport http feedbk https://mcp.feedbk.ai/mcp, gemini mcp add feedbk --url ..., codex mcp add feedbk --url ..., as a VS Code HTTP server entry, or as a Claude Desktop custom connector. ChatGPT support needs a Pro, Team, Enterprise or Edu subscription and Developer Mode enabled under advanced settings. A local install is Python 3.10 or newer with the feedbk-skill-mcp package, and gives up deployment and shareable links. MIT licensed.
Setup effort
One command — claude mcp add --transport http feedbk https://mcp.feedbk.ai/mcp
USE CASES
Turning a research question into a running survey
Describe what you want to learn; the guide is built, deployed, and comes back as a link you can share.
Finding out why customers cancel
Ask for an interview on the topic and let the AI moderator probe each answer rather than accepting the first sentence.
Drafting a guide without publishing it
Use the local install to create and export the guide, then decide separately whether to deploy it.
INSTALLATION
Connect your client
Server setup
Setup
Claude Code:
claude mcp add --transport http feedbk https://mcp.feedbk.ai/mcpGoogle Gemini CLI:
gemini mcp add feedbk --url https://mcp.feedbk.ai/mcpOpenAI Codex CLI:
codex mcp add feedbk --url https://mcp.feedbk.ai/mcpClaude Desktop: Settings -> Connectors -> Add Custom Connector, Name Feedbk, URL https://mcp.feedbk.ai/mcp
VS Code: add the mcp.servers.feedbk http entry shown in the config block
Hosted endpoint
https://mcp.feedbk.ai/mcpAdd this hosted endpoint to your MCP client.
MCP Clients
Claude Code
claude mcp add --transport http feedbk https://mcp.feedbk.ai/mcpVS Code
{
"servers": {
"feedbk": {
"type": "http",
"url": "https://mcp.feedbk.ai/mcp"
}
}
}Gemini CLI
gemini mcp add feedbk --url https://mcp.feedbk.ai/mcpCodex
codex mcp add feedbk --url https://mcp.feedbk.ai/mcp